Using a large citizen science dataset to uncover diverse patterns of elevational migration in Himalayan birds
收藏NIAID Data Ecosystem2026-05-02 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.9cnp5hqvm
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Elevational migration is well-documented in montane birds, yet large-scale patterns outside the Americas remain understudied. Using eBird data, we analysed the elevational ranges of 377 Himalayan bird species across breeding and non-breeding periods. We describe five elevational migration patterns which broadly include post-breeding upslope and downslope migration. Most high elevation breeders (65-75%) were downslope migrants, which were further subdivided into four distinct patterns: “displace”, “shift”, “expand”, and “contract”. Notably, 30% of species show partial migration (expand and contract). The same species often show different migration patterns in the eastern and western Himalayas indicating significant intraspecific variation, determined by local biotic and abiotic conditions. Specialised dietary guilds like invertivores were more likely to show shift or displace migration, potentially tracking seasonally fluctuating food resources. Generalists like omnivores and human commensals were more likely to be resident. Species found in open habitats were also more likely to show shift and displace migration, as open habitats have more pronounced exposure to adverse climate conditions which many species are unable to withstand. Territorial birds were largely non-migratory, most likely to retain high quality breeding territories. These migration patterns, shaped by the bounded nature of mountain ranges is useful for understanding elevational migration globally.
Methods
This data is freely available on eBird (EBD Dataset) and data can be requested via https://ebird.org/data/download. Data uploaded are eBird (EBD) datasets up to the month of April 2024 for Bhutan and the Indian states of Himachal Pradesh, Uttarakhand, West Bengal, Sikkim, Arunachal Pradesh and the Union Territories of Jammu and Kashmir and Ladakh. The data was processed in RStudio, code for processing the data and reproducing the analysis in the manuscript has been uploaded.
创建时间:
2025-05-22



